Organizations today are facing a number of new challenges and opportunities related to the deployment and use of Big Data concepts, processes and technology. A number of trends and key directions are starting to develop, creating the main focus areas that business and IT leadership should consider as they approach deploying and operating Big Data for their organization.

Leveraging Data

One of the keys to effectively leveraging and realizing the value of Big Data is to understand some of the approaches you need to take. Whether you are trying to get closer to your customers or to your business, points to consider include:

Aggregate – What are the standards or principals you need to apply to efficiently and effectively drive aggregation? Look at whether you have setup the standards and controls so aggregation is not just efficient, but also cost effective.

Organize – Have you organized your approach to Data in a way that benefits your customer and your organization? Most organizations have not considered using external validations, such as webex based customer seminars or Google analytics that look at, for example, sales data.

Apply - What are you doing to apply the data and tools required to succeed in this space? One consideration is looking at the tools you are using today and considering how you can drive consolidation and savings, in order to fund a new focus on Big Data and analytics.

Delivering Products that matter

The approach you take will not make a difference if you do not have a grounded view or strategic vision to where you want to go. The key trends and focus areas we are seeing today include:

Support Collaboration – Using Big Data to support collaboration, both internal and customer focused.

Drive Analysis – Improving analysis and the current approaches are myriad. Spotting patterns in data and framing relevant analysis is more evident. Using new tools such as semantic data toolsets, Hadoop and Cloud Services provide new analysis capabilities and opportunities.

Increase Efficiency – Look at the new products you are going to deliver. Are they able to increase the efficiency of your customer services or will the products improve the internal services you provide?

Big Data Tools

The opportunities related to using the tools of Big Data may not be evident. The world of mainframe computing and using ETL to address massive amounts of data has changed. Take a look to see if you can use tools like Hadoop to drive savings. Are you able to reduce of eliminate ETL (extract, transfer, load) altogether? Can the new tools reduce mainframe costs? How about embracing open source tools and see how you could replace Unix with Linux? Using the new tools of Big Data could provide the platform for innovation, consolidating databases and driving significant efficiencies.

To find out more about how to use these approaches, don’t hesitate to contact us.

One of the challenges we now face is how best to understand the ‘ x as a service’ marketplace, the key concepts and economic benefits where services can increase organizational capability and save money. Current advances in ‘x as a service’ capabilities provide organizations with the ability to look at addressing and solving their traditional challenges in new ways. Some of the best examples include the following:

Improving IT Asset Management and Streamlined Operations

Delivery of Infrastructure as a Service can increase resource utilization and reduce overhead. For example, infrastructure is often isolated or silo’ed based on a “line of business” model. New cloud capabilities move the “isolated” infrastructures into a global cloud, and they now function as if they are in one integrated data center. The logic that was used to build the current independent model is no longer relevant or cost effective. The advantage is that you can quickly ramp up infrastructure capability and start a new venture with limited lead time and fewer constraints. The service provider delivers this as a service, allowing you to focus on the requirements. A key question to ask the service provider is their ability to deliver the financial accounting, charge back and metering model you require to make chargeback information visible to your business customer.

Software Development and Testing

One of the constant challenges faced by projects is the ability of IT to meet the demands for new environments. IT is often challenged with budget constraints, long lead times to provision environments and often conflicts with multiple other competing environments. All of this leads to project slippage, delaying delivery and a lot of frustration. One of the key benefits with the ‘’x as a service provider’ is that the provider can provide the development teams with the ability to provision their own environment reducing time and the overall IT workload. In the end, this means faster turnaround and ultimately shortens delivery time for the business.

Scalability

IT is often challenged to provide solutions that accurately react to the highs and lows of demand, spikes in traffic and consistent performance, at the time when it is critically needed. The quick solution often deployed includes increasing investments in infrastructure and resources, without a guarantee that the investment will deliver results. With Cloud, organizations can increase capability and save money using the ‘x as a service’ approach that automates requests for new computing and storage, and adjusts for seasonal variability. Expansion can be immediate, leveraging the public cloud for extra capacity. The associated reduction in capital expenditures and infrastructure can be realized almost immediately.

These are just a few of the examples of the use of IT services to increase organizational capability and save money. Our experience is that the marketplace is delivering a wide range of solutions and capabilities, with new and more innovative solutions to address the traditional challenges outlined above.

Embrace the changes in ’x as service’ solutions and seek ways to solve your current issues!

The time has come (some would say it is long overdue) to seriously consider new operating models for Insurance and Financial Services. I may be committing some type of heresy or creating confusion by mentioning both industries in the same sentence, but as an implementation and strategic advisor/partner for both industries, the truth is not pretty. The competitive and survival threats to both industries are real and becoming more evident in our evolving culture of expanded consumer awareness and increasing demands for customer transparency into the operating models of both Insurance and Financial Services companies. Although the 2008 recession opened the window into some of the business practices of both groups, there is a clear need to do much more than meet current legal and regulatory requirements of Basel III and Dodd-Frank.

Examples of threats that are going to drive new operating models in both the Financial Services and Insurance industries include:

Consumerization: The mobility and iPad revolution has arrived and has already moved beyond the current capability of most firms. Firms must “get in the game” and offer content and services that are valuable to the consumer. This is the real ‘game’ and the real threat. The ability to successfully initiate and complete transactions in limited time and with a high level of accuracy is troubling. When the capability does not exist, the consumer will move on to the next best provider. The lack of ‘best in class' capability for today’s consumers of banking and insurance products has become a reflection of the lack of current capabilities of senior leadership in operational delivery. Rather than radically change the operating model in response to demand (remember the use of the assembly line for automotive industry?) the operating models continue to represent an inability to quickly grasp customer demands and turn them into consumable products and services.

Data Management: Yes, ‘Big Data” is real and there is a lot of talk about its capabilities and how the world of data management and “Big Data” will change the world. Even so, there is little discussion about the use of data management and the impact is has on the operating models in Insurance and Financial Services. In a few cases, new approaches for data are layered on top of existing practices and operating models, causing the models to expand and create new operating processes, new operating controls and positively impact the overall risk framework. What is not happening is the rationalization and shut down of in-effective data processes and practices and the requisite changes to the operating model in both industries. A great example from my life is the interaction between looking at your online bank statement and calling the help line. What may happen is that data management will not be adequately addressed by either Insurance or Financial Services and the result will be complexity and consumer angst.

Transparency: As a consumer and a taxpayer who has funded several of the firms bailed out in 2008 with little or no insight into how the bailout money was spent and how the firms are actually operating today, the threat/value of transparency is very real. Consumers will continue to want transparency into billings and fees and the key items of service. But in addition, consumers, partners and providers of services to the Insurance and Financial Services industries will be clamoring for transparency into the use of capital, the realization of strategic goals for decreasing internal expense and holding management accountable for the same. How in this age of transparency can Insurance and Financial Service firms hold negotiations or reward participants in a financial transaction with limited transparency to their stockholders and the taxpayers who fund them? Transparency of data, transactions, leadership, decisions key funded ventures, and strategic partnerships are not threats to competition or confidentiality….they are threats to the survival of the Insurance and Financial Service firms, if not managed effectively with the stockholders and taxpayers who offer support.

These are just three examples of why new operating models are needed for both industries. Our experience and insight into both Insurance and Financial Services has proven that over the years, the operating models have evolved to in-effective monoliths that reflect corporate structures and not the consumer. Just as rapid as the “Occupy Wall Street” movement in 2011 and the KONY 12 video spread in 2012, the threats identified above will spread and will drive change to the operating models that exist today.

We all know the saying "change is never easy," and have probably heard this when embarking on a new initiative or program. You may be calling the team to action or working to roll out a new program that will face significant challenges. In order to prepare for the change and take control of the situation, think about these key areas and what you can do:

Governance – The governance model needs to cover both IT and the business. Instead of defining a governance model and rolling it out to your business partners, why not engage your partners in a quick worksession or interview exercise to define what each party wants to see as a part of governance. For example, a common, combined taxonomy for measurement across both IT and the business can go a long way in running an effective governance model that drives value from the IT organization to the business.

Value – Understanding the contribution of each partner in the delivery model is critical. Bringing together the combined team to define the value proposition and the desired outcomes will clarify objectives and help when faced with new demands and the need to re-prioritize projects, activities and other initiatives. A clear definition of value that can be periodically revisited when demand changes can be an effective tool to minimize the noise and keep the team on track.

Measurement – In order to prepare for the change, one of the most challenging aspects is how to measure success? What does successful completion of the initiative look like? Take a first step and forecast what you think the measurements should be. Then take the next step to determine if you can actually deliver the measurement, by collecting the data and then presenting it in a simple and concise manner. You may have a formula and a specification for a great measurement but gathering the data, analyzing the data, or explaining the measure may be more difficult or costly than the ultimate value of the measure. Strive for simplicity, look for measures that are not only practical, and look for fewer measures, not more.

Accountability – Understanding what each group brings to the table is critical and a great team exercise. A quick roundtable to get the opinion as to the role of each team member will probably demonstrate that accountability is not clear. Take the time before you begin the initiative to clearly identify accountability. Walking through a few examples and sample change scenarios up front will go a long way and help to eliminate confusion.

Data can be captured everywhere on the web, but is there any intelligence that interprets this data and makes it available for critical decision making?

And what do I mean by critical decision making? Those decisions that you have to make when you either build that new mobile app or launch a social media program for your clients. These are the decisions that give you the best return on your investment.

You shouldn’t feel like a metrics failure. In fact, you join most of those struggling with the overwhelming amount of data and lack of information in the web analytics universe.

So, what is the real problem? Part of the problem is that data is reallyeasy to get. In fact, you can add, subtract, multiply and divide this data to satisfy every potential question about the web. The rest of the problem relates to the old adage - just because you CAN, doesn’t mean you SHOULD.

So…why do we?

Like overachieving hoarders, we collect data and stack reports believing that, someday, an executive will ask a question about the web that can be found buried in your metrics. We continue this behavior until the monthly report takes three weeks to build and disseminate. We avoid being nimble and agile, because we might “miss something." We collect everything because we are afraid of making the choices about what is important. We fear the answer that we might have to give the executive: “We made the decision that collecting and analyzing the data to answer your question was not a priority, or not cost-effective.”

The key to all of this, of course, is to make logical, rational decisions about what to collect and understand why you are collecting it, by engaging the business and responding to their information needs. These have to be the metrics that give us insight into what functionality we fund on the web to get the best ROI.

There is a simple question that you can ask yourself to determine if the metrics you are collecting have any significance for your business: What action(s) will you take, now that you have the information captured in this metric? Based on this simple question, if the answer is that the metric is “nice to know,” or it was suggested by a consultant, or “we have always measured this,” or it just flat out “sounds important,” but still doesn’t result in action, then it is just another overhead activity that you can do without.

We don’t want metrics just because we can collect them, or they are nice to have. We want them to relate to business questions that need answers, ones that then lead to actions that positively impact the bottom line. If you can’t link a metric or small group of metrics to a specific business question, then stop collecting them!

One last thing to keep in mind…..metrics should be dynamic. Yes, I understand that need to normalize data and capture trends over time. But as the maturity of your websites evolve, as well as the maturity of the business in leveraging the technologies, your information needs will change. Your metrics should change too.

One of the tricks to a successful contract and vendor relationship is the actual strength and flexibility of the contract between both parties. Aside from the typical ways we setup contracts and use industry standards, we also need to consider the key areas that we should be watching out for… or better yet… what are the "gotcha’s" that you need to be concerned about?

If I was explaining this to someone in a leadership role, I’d want to make sure the following list was incorporated into our discussion. Narrowing this down to 14 areas was tough, but here goes:

Vendor Capacity – Do you know what the vendor has in place today, what is planned to support future deployments?

Increase in Volume – Can vendor delivery scale to meet increased demand or services? For example, if you do increase the volume of work, have you pre-defined your expectations for pricing and delivery?

Transition – Has the transition been defined with explicit deliverables for pre-transition, transition and post-transition.

Current Staff – What will you do with the staff currently performing services? Will they become part of or integrate with vendor delivery? Who is driving continuity and knowledge transfer?

Contract Changes – How will both parties deal with changes to the contract?

Vendor or Client Default – If something happens, has the model for remediation been defined prior to the contract execution?

3rd Party Default – Has the model for remediation been defined if a supplier in the chain of delivery defaults or is not able to provide services?

Proprietary or Confidential Content – How will the vendor maintain the confidentiality of content across the delivery model?

Governance – Is there a complete governance framework in place for managing the execution of the contract for all parties - you, the vendor and any 3rd party suppliers?

Contractual Structure – Has the contract been structured with the right tools to sustain and address prospective areas of risk?

Data Privacy and Security – Has the combined team addressed privacy and security requirements in a proactive and continual manner that does not pose risks?

Risk – Have you looked at each operational aspect of the contract and identified what actions would be necessary if the risk becomes a reality?

Communication – Does the contract address both internal and external requirements, with a pre-defined approach for effective communication and change management?

Lack of Investment or Commitment – Do you have the appropriate commitment for all parties to address oversight, contract commitment and the proper access to required tools? For example, what does your contract specify regarding 3rd party software access rights?

The items above are just a handful of key considerations. There are many more items to consider and take into account when delivering a strong and flexible contract between both parties.